Abstract: Capabilities and features of a modem are specified in accordance with descriptions of applications to be executed on the modem. The specification of the modem using individual applications enables the verification of intended performance based on the individual applications, simplifying the testing and assuring of the modem. To that end, a method implemented by a cloud computing resource (CCR) includes receiving, by the CCR, a description of an application supported by a modem. A dataflow fragment (DFF) for the application is generated by the CCR and is stored by the CCR in a memory, The DFF is retrieved and provided to the modem based on a description of the modem.

Abstract: Technology for providing data to a processing unit is disclosed. A computer processor may be divided into a master processing unit and consumer processing units. The master processing unit at least partially decodes a machine instruction and determines whether data is needed to execute the machine instruction. The master processing unit sends a request to memory for the data. The request may indicate that the data is to be sent from the memory to a consumer processing unit. The data sent by the memory in response to the request may be stored in local read storage that is close to the consumer processing unit for fast access. The master processing unit may also provide the machine instruction to the consumer processing unit. The consumer processing unit may access the data from the local read storage and execute the machine instruction based on the accessed data.

Abstract: A system and method for variable lane architecture includes memory blocks located in a memory bank, one or more computing nodes forming a vector instruction pipeline for executing a task, each of the computing nodes located in the memory bank, each of the computing nodes executing a portion of the task independently of other ones of the computing nodes, and a global program controller unit (GPCU) forming a scalar instruction pipeline for executing the task, the GPCU configured to schedule instructions for the task at one or more of the computing nodes, the GPCU further configured to dispatch an address for the memory blocks used by each of the computing nodes to the computing nodes.

Abstract: A data warehouse engine (DWE) includes a central processing unit (CPU) core and a first data organization unit (DOU), where the first DOU is configured to aggregate read operations. The DWE also includes a first command queue coupled between the CPU core and the first DOU, where the first command queue is configured to convey commands from the CPU core to the first DOU.

Abstract: A computation system-on-a-chip (CSoC) includes a first scalable distributed real-time Data Warehousing (sdrDW) engine and a network interface coupled to the first sdrDW engine, where the network interface is coupled to an interconnect, and where the CSoC is configured to transmit a task request over the interconnect to a first networked bulk storage controller (NBSC) requesting that a task be performed on a bulk storage medium.

Abstract: A system and method for variable lane architecture includes memory blocks located in a memory bank, one or more computing nodes forming a vector instruction pipeline for executing a task, each of the computing nodes located in the memory bank, each of the computing nodes executing a portion of the task independently of other ones of the computing nodes, and a global program controller unit (GPCU) forming a scalar instruction pipeline for executing the task, the GPCU configured to schedule instructions for the task at one or more of the computing nodes, the GPCU further configured to dispatch an address for the memory blocks used by each of the computing nodes to the computing nodes.

Abstract: A system and method for variable lane architecture includes memory blocks located in a memory bank, one or more computing nodes forming a vector instruction pipeline for executing a task, each of the computing nodes located in the memory bank, each of the computing nodes executing a portion of the task independently of other ones of the computing nodes, and a global program controller unit (GPCU) forming a scalar instruction pipeline for executing the task, the GPCU configured to schedule instructions for the task at one or more of the computing nodes, the GPCU further configured to dispatch an address for the memory blocks used by each of the computing nodes to the computing nodes.

Abstract: A data streaming unit (DSU) and a method for operating a DSU are disclosed. In an embodiment the DSU includes a memory interface configured to be connected to a storage unit, a compute engine interface configured to be connected to a compute engine (CE) and an address generator configured to manage address data representing address locations in the storage unit. The data streaming unit further includes a data organization unit configured to access data in the storage unit and to reorganize the data to be forwarded to the compute engine, wherein the memory interface is communicatively connected to the address generator and the data organization unit, wherein the address generator is communicatively connected to the data organization unit, and wherein the data organization unit is communicatively connected to the compute engine interface.

Abstract: Technology for providing data to a processing unit is disclosed. A computer processor may be divided into a master processing unit and consumer processing units. The master processing unit at least partially decodes a machine instruction and determines whether data is needed to execute the machine instruction. The master processing unit sends a request to memory for the data. The request may indicate that the data is to be sent from the memory to a consumer processing unit. The data sent by the memory in response to the request may be stored in local read storage that is close to the consumer processing unit for fast access. The master processing unit may also provide the machine instruction to the consumer processing unit. The consumer processing unit may access the data from the local read storage and execute the machine instruction based on the accessed data.

Abstract: A cache and a method for operating a cache are disclosed. In an embodiment, the cache includes a cache controller, data cache and a delay write through cache (DWTC), wherein the data cache is separate and distinct from the DWTC, wherein cacheable write accesses are split into shareable cacheable write accesses and non-shareable cacheable write accesses, wherein the cacheable shareable write accesses are allocated only to the DWTC, and wherein the non-shareable cacheable write accesses are not allocated to the DWTC.

Abstract: A cache and a method for operating a cache are disclosed. In an embodiment, the cache includes a cache controller, data cache and a delay write through cache (DWTC), wherein the data cache is separate and distinct from the DWTC, wherein cacheable write accesses are split into shareable cacheable write accesses and non-shareable cacheable write accesses, wherein the cacheable shareable write accesses are allocated only to the DWTC, and wherein the non-shareable cacheable write accesses are not allocated to the DWTC.

Abstract: A method includes obtaining, by a first processor, a first software architecture description file and obtaining, by the first processor, a platform independent model file. The method also includes obtaining, by the first processor, a platform architecture definition file and performing, by the first processor, a first source-to-source compilation in accordance with the first software architecture description file, the platform independent model file, and the platform architecture definition file, to produce generated interface code. Additionally, the method includes generating, by the first processor, run time code, in accordance with the generated interface code and running, by a second processor in real time, the run time code.

Abstract: A data warehouse engine (DWE) includes a central processing unit (CPU) core and a first data organization unit (DOU), where the first DOU is configured to aggregate read operations. The DWE also includes a first command queue coupled between the CPU core and the first DOU, where the first command queue is configured to convey commands from the CPU core to the first DOU.

Abstract: A data streaming unit (DSU) and a method for operating a DSU are disclosed. In an embodiment the DSU includes a memory interface configured to be connected to a storage unit, a compute engine interface configured to be connected to a compute engine (CE) and an address generator configured to manage address data representing address locations in the storage unit. The data streaming unit further includes a data organization unit configured to access data in the storage unit and to reorganize the data to be forwarded to the compute engine, wherein the memory interface is communicatively connected to the address generator and the data organization unit, wherein the address generator is communicatively connected to the data organization unit, and wherein the data organization unit is communicatively connected to the compute engine interface.

Abstract: A computation system-on-a-chip (CSoC) includes a first scalable distributed real-time Data Warehousing (sdrDW) engine and a network interface coupled to the first sdrDW engine, where the network interface is coupled to an interconnect, and where the CSoC is configured to transmit a task request over the interconnect to a first networked bulk storage controller (NBSC) requesting that a task be performed on a bulk storage medium.

Abstract: A system and method for variable lane architecture includes memory blocks located in a memory bank, one or more computing nodes forming a vector instruction pipeline for executing a task, each of the computing nodes located in the memory bank, each of the computing nodes executing a portion of the task independently of other ones of the computing nodes, and a global program controller unit (GPCU) forming a scalar instruction pipeline for executing the task, the GPCU configured to schedule instructions for the task at one or more of the computing nodes, the GPCU further configured to dispatch an address for the memory blocks used by each of the computing nodes to the computing nodes.

Abstract: A method includes receiving, by a system on a chip (SoC) from a logically centralized controller, configuration information and reading, from a semantics aware storage module of the SoC, a data block in accordance with the configuration information. The method also includes performing scheduling to produce a schedule in accordance with the configuration information and writing the data block to an input data queue in accordance with the schedule to produce a stored data block. Additionally, the method includes writing a tag to an input tag queue to produce a stored tag, where the tag corresponds to the data block.

Abstract: A processor includes a first and second execution unit each of which is arranged to execute multiply instructions of a first type upon fixed point operands and to execute multiply instructions of a second type upon floating point operands. A register file of the processor stores operands in registers that are each addressable by instructions for performing the first and second types of operations. An instruction decode unit is responsive to the at least one multiply instruction of the first type and the at least one multiply instruction of the second type to at the same time enable a first data path between the first set of registers and the first execution unit and to enable a second data path between a second set of registers and the second execution unit.

Abstract: A real request from a CPU to the same memory bank as a prior prefetch request is transmitted to the per-memory bank logic along with a kill signal to terminate the prefetch request. This avoids waiting for a prefetch request to complete before sending the real request to the same memory bank. The kill signal gates off any acknowledgement of completion of the prefetch request. This invention reduces the latency for completion of a high priority real request when a low priority speculative request to a different address in the same memory bank has already been dispatched.

Abstract: A prefetch controller implements an upgrade when a real read access request hits the same memory bank and memory address as a previous prefetch request. In response per-memory bank logic promotes the priority of the prefetch request to that of a read request. If the prefetch request is still waiting to win arbitration, this upgrade in priority increases the likelihood of gaining access generally reducing the latency. If the prefetch request had already gained access through arbitration, the upgrade has no effect. This thus generally reduces the latency in completion of a high priority real request when a low priority speculative prefetch was made to the same address.